Data items are versioned to maximize data integrity in failure scenarios without compromising availability of the system

Each node is independent of other nodes with no central point of failure or coordination

Good single node performance: you can expect 10-20k operations per second depending on the machines, the network, the disk system, and the data replication factor

Support for pluggable data placement strategies to support things like distribution across data centers that are geographically far apart.

It is used at LinkedIn by numerous critical services powering a large portion of the site.

Voldemort is a distributed data store that is designed as a key-value store used by LinkedIn for high-scalability storage. It is named after the fictional Harry Potter villain Lord Voldemort.

It is neither an object database, nor a relational database. It does not try to satisfy arbitrary relations and the ACID properties, but rather is a big, distributed, fault-tolerant, persistent hash table.A 2012 study comparing systems for storing application performance management monitoring data reported that Voldemort, Cassandra, and HBase offered linear scalability in most cases, with Voldemort having the lowest latency and Cassandra having the highest throughput.